Network-side Result Analysis

Network-side performance result analysis is a follow-up to Client and Server performance analysis and tuning efforts that I have discussed in the previous articles (Performance Test Result Analysis Basic Level and Performance TestResult Analysis Intermediate Level). Once you tested and optimized the client and server-side performance but still not getting the desired result, then look at the … Read more

Error Graph

Error Graph

This is one of the basic graphs and frequently use to debug the performance bottleneck. Error graph provides details about the type of errors and the time when they occurred. Error graph could be the first point to kick-off the investigation of performance issue. It helps to categorize the error using response code. If the … Read more

Throughput Graph

Throughput Graph

This has been noticed that the throughput graph is always less attentive. The reason could be either a performance tester does not understand its importance or does not care about it because it is not included in the NFRs. Of course, it is true that Throughput does not fall under the core performance metric category … Read more

Transactions per second Graph

TPS Graph Analysis

In a performance test script, transaction refers to a group of requests which are sent to the server. A simple webpage may contain multiple requests which are associated with the components available on it. When a user does any action like hitting a button on the webpage then these requests (sync or async) are wrapped … Read more

Response Time Graph

Response Time Graph

Response time graph gives a clear picture of overall time including requesting a page, processing the data and getting the response back to the client. As per PTLC (Performance Test Life Cycle), the Response time NFRs should be discussed and agreed during the NFR gathering phase and then compared with actual response time which is … Read more

User Graph

Running Vuser Graph

A User Graph provides complete information about load pattern during the test. This graph helps to identify: When did the user load start? What were the user ramp-up and ramp-down pattern? When did the steady-state start? How many users were active at a particular time? When was the user exited from the test? In runtime … Read more